Field of the Invention
The present invention relates to information handling systems. More specifically, embodiments of the invention relate to extrapolating sarcasm or irony using machine learning based linguistic analysis.
Description of the Related Art
As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option available to users is information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, airline reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software components that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.
An ambiguous utterance may be defined as an utterance that has uncertain meaning in the context it appears. Ambiguous utterances include sarcastic utterances and ironic utterances. Although there are other types of ambiguity like generality, indexicality, polysemy, or vagueness, the present disclosure is mainly concerned with sarcasm and irony. A sarcasm utterance may be defined as a sharp, bitter, mocking, or cutting expression or remark; a bitter gibe or taunt. Sarcasm may employ ambivalence, although sarcasm is not necessarily ironic. One aspect of sarcasm is that sarcasm is present in the spoken word and manifested chiefly by vocal inflections. The sarcastic content of a statement often depends upon the context in which it appears. Ironic utterances may be defined as utterances that in their surface form convey the opposite of their intended meaning. Some ironic utterances may also be sarcasm utterances.
Identifying ambiguous utterances is often important to providing accurate interpretation of a text or spoken passage. Accordingly, doing so is a common prerequisite for performing more complex Natural Language Processing (NLP) processing tasks. However, it is challenging to automatically detect ambiguous utterances. One reason for this difficulty is an absence of accurately-labeled naturally occurring utterances that can be used to train machine learning systems. The lack of training corpora is exacerbated by the rapidly-changing nature of language and the constant invention of new forms of utterances derived from slang, loan words, or neologisms. Sarcasm and irony are well studied phenomena in linguistics, psychology and cognitive science. However, in text mining literature, automatic detection of ambiguous utterances is considered a difficult problem. In the context of spoken dialogues, automatic detection of utterances has relied primarily on speech-related cues such as laughter and prosody.
Accordingly, it would be desirable to facilitate the identification of ambiguous utterances including sarcastic utterances and ironic utterances.